Research

A machine learning based fetal monitoring system to predict and prevent fetal hypoxia

Grant

Authors
Authors
Authors
Bonnie Zell
https://www.delfina.com/resource/ml-based-fetal-monitoring-to-predict-prevent-hypoxia

Principal Investigator: Bonnie Zell

Funding Agency: National Institutes of Health

Project Narrative: This project will deliver a new system to offer new evidence-based insights to physicians caring for pregnant women to improve health outcomes for their babies. By using advanced computational approaches, this system will be able to predict adverse events like stillbirth and brain damage to enable physicians to intervene in a timely way to preemptively improve outcomes. The output of this project will be an intelligent software monitoring system for patients in labor, which will augment the capabilities of obstetricians and improve well-being for newborn babies.

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Research

A machine learning based fetal monitoring system to predict and prevent fetal hypoxia

Grant

Authors
Authors
Authors
Bonnie Zell
https://www.delfina.com/resource/ml-based-fetal-monitoring-to-predict-prevent-hypoxia

Principal Investigator: Bonnie Zell

Funding Agency: National Institutes of Health

Project Narrative: This project will deliver a new system to offer new evidence-based insights to physicians caring for pregnant women to improve health outcomes for their babies. By using advanced computational approaches, this system will be able to predict adverse events like stillbirth and brain damage to enable physicians to intervene in a timely way to preemptively improve outcomes. The output of this project will be an intelligent software monitoring system for patients in labor, which will augment the capabilities of obstetricians and improve well-being for newborn babies.

READ NOW

Research

A machine learning based fetal monitoring system to predict and prevent fetal hypoxia

Grant

Authors
Authors
Authors
Bonnie Zell
https://www.delfina.com/resource/ml-based-fetal-monitoring-to-predict-prevent-hypoxia

Principal Investigator: Bonnie Zell

Funding Agency: National Institutes of Health

Project Narrative: This project will deliver a new system to offer new evidence-based insights to physicians caring for pregnant women to improve health outcomes for their babies. By using advanced computational approaches, this system will be able to predict adverse events like stillbirth and brain damage to enable physicians to intervene in a timely way to preemptively improve outcomes. The output of this project will be an intelligent software monitoring system for patients in labor, which will augment the capabilities of obstetricians and improve well-being for newborn babies.

READ NOW

Research

A machine learning based fetal monitoring system to predict and prevent fetal hypoxia

Grant

Authors
Authors
Authors
Bonnie Zell
https://www.delfina.com/resource/ml-based-fetal-monitoring-to-predict-prevent-hypoxia

Principal Investigator: Bonnie Zell

Funding Agency: National Institutes of Health

Project Narrative: This project will deliver a new system to offer new evidence-based insights to physicians caring for pregnant women to improve health outcomes for their babies. By using advanced computational approaches, this system will be able to predict adverse events like stillbirth and brain damage to enable physicians to intervene in a timely way to preemptively improve outcomes. The output of this project will be an intelligent software monitoring system for patients in labor, which will augment the capabilities of obstetricians and improve well-being for newborn babies.

READ NOW

Research

A machine learning based fetal monitoring system to predict and prevent fetal hypoxia

Grant

https://www.delfina.com/resource/ml-based-fetal-monitoring-to-predict-prevent-hypoxia

Principal Investigator: Bonnie Zell

Funding Agency: National Institutes of Health

Project Narrative: This project will deliver a new system to offer new evidence-based insights to physicians caring for pregnant women to improve health outcomes for their babies. By using advanced computational approaches, this system will be able to predict adverse events like stillbirth and brain damage to enable physicians to intervene in a timely way to preemptively improve outcomes. The output of this project will be an intelligent software monitoring system for patients in labor, which will augment the capabilities of obstetricians and improve well-being for newborn babies.

READ NOW

Research

A machine learning based fetal monitoring system to predict and prevent fetal hypoxia

Grant

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https://www.delfina.com/resource/ml-based-fetal-monitoring-to-predict-prevent-hypoxia